LAPSE:2023.16115
Published Article

LAPSE:2023.16115
A Study on the Impact of Distance-Based Value Loss on Transmission Network Power Flow Using Synthetic Networks
March 3, 2023
Abstract
This paper presents a methodology for rapid generation of synthetic transmission networks and uses it to investigate how a transmission distance-based value loss affects the overall grid power flow. The networks are created with a graph theory-based method and compared to existing energy systems. The power production is located on these synthetic networks by solving a facility location optimization problem with variable distance-based value losses. Next, AC power flow is computed for a snapshot of each network using the Newton−Raphson method and the transmission grid power flow is analyzed. The presented method enables rapid analysis of several grid topologies and offers a way to compare the effects of production incentives and renewable energy policies in different network conditions.
This paper presents a methodology for rapid generation of synthetic transmission networks and uses it to investigate how a transmission distance-based value loss affects the overall grid power flow. The networks are created with a graph theory-based method and compared to existing energy systems. The power production is located on these synthetic networks by solving a facility location optimization problem with variable distance-based value losses. Next, AC power flow is computed for a snapshot of each network using the Newton−Raphson method and the transmission grid power flow is analyzed. The presented method enables rapid analysis of several grid topologies and offers a way to compare the effects of production incentives and renewable energy policies in different network conditions.
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Keywords
energy policies, optimal power production positioning, power system planning, synthetic network data
Subject
Suggested Citation
Rantaniemi J, Jääskeläinen J, Lassila J, Honkapuro S. A Study on the Impact of Distance-Based Value Loss on Transmission Network Power Flow Using Synthetic Networks. (2023). LAPSE:2023.16115
Author Affiliations
Rantaniemi J: School of Energy Systems, LUT University, Yliopistonkatu 34, 53850 Lappeenranta, Finland
Jääskeläinen J: Department of Mechanical Engineering, School of Engineering, Aalto University, Otakaari 4, 02150 Espoo, Finland
Lassila J: School of Energy Systems, LUT University, Yliopistonkatu 34, 53850 Lappeenranta, Finland
Honkapuro S: School of Energy Systems, LUT University, Yliopistonkatu 34, 53850 Lappeenranta, Finland [ORCID]
Jääskeläinen J: Department of Mechanical Engineering, School of Engineering, Aalto University, Otakaari 4, 02150 Espoo, Finland
Lassila J: School of Energy Systems, LUT University, Yliopistonkatu 34, 53850 Lappeenranta, Finland
Honkapuro S: School of Energy Systems, LUT University, Yliopistonkatu 34, 53850 Lappeenranta, Finland [ORCID]
Journal Name
Energies
Volume
15
Issue
2
First Page
423
Year
2022
Publication Date
2022-01-07
ISSN
1996-1073
Version Comments
Original Submission
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PII: en15020423, Publication Type: Journal Article
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LAPSE:2023.16115
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https://doi.org/10.3390/en15020423
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Mar 3, 2023
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